Principal Data Engineer - Data Strategy & Architecture

Fifth Third Bank; Cincinnati (OH); Presencial; USD 150 000 - 190 000; Tempo integral

Resumo da oferta

Fifth Third Bank is seeking a Principal Data Engineer to design and build scalable data platforms and tools that enable secure, governed data across on-premises and cloud environments. You will mentor teams, define engineering standards, and drive strategic data initiatives across multiple agile groups.

The role emphasizes data product thinking, risk management, and AI-assisted development to improve productivity, testing, and documentation while delivering trusted data assets for analytics and

Responsabilidades

• Responsible for design, development, and support of scalable data solutions, APIs, tools, and processes that enable rapid delivery of business capabilities across both traditional and modern data platforms.
• Work closely with IT application teams, Enterprise Architecture, infrastructure, information security, and LOB stakeholders to translate business and technical strategies into data-driven solutions, shape technical direction, and influence outcomes across multiple teams within a business or data domain with added impact across the broader organization.
• Act as a principal technical expert and trusted advisor addressing the most complex problems related to system and application design, performance, integration, security, and delivery.
• Conduct research and development based on current trends and technologies related to the banking industry, data engineering and architecture, data security, AI-readiness, and related topics, and translate relevant findings into practical improvements.
• Build and maintain CI/CD pipelines and self-service deployment tools to streamline development and operations.
• Evaluate data and software products, providing documented recommendations to improve capabilities.
• Lead ownership of the most complex and strategically important data solutions throughout their lifecycle, including design, development, testing, deployment, monitoring, operational support, modernization, and retirement, while defining and driving engineering standards across multiple teams.
• Provide support and troubleshooting for data pipelines and platforms, including participation in incident response and resolution for critical production issues.
• Lead strategic technical initiatives across multiple teams, including legacy system modernization, data pipeline improvements, monitoring, and documentation, while proactively identifying cross-team dependencies, risks, and barriers to delivery.
• Optimize and automate data pipelines for efficiency, scalability, observability, and performance.
• Develop and maintain automated testing, validation, reconciliation, and data quality controls to ensure reliable, trusted, and production-ready data solutions.
• Leverage approved AI-assisted engineering capabilities to improve productivity, code quality, testing, documentation, and problem solving, while supporting the delivery of trusted data assets for analytics, artificial intelligence, and machine learning solutions.
• Apply a data product mindset by managing the full lifecycle of data assets and ensuring appropriate ownership, quality, discoverability, documentation, lineage, and governance.
• Provide technical leadership, mentoring, coaching, and knowledge sharing across multiple teams, raising engineering competencies and contributing to greater effectiveness across the broader business or data domain and organization.
• Drive prioritization, escalation, and resolution of competing technical demands and strategic dependencies across multiple teams.
• Lead delivery of strategic, high-impact data solutions across multiple Agile teams through close collaboration with product owners and stakeholders, proactively removing cross-team barriers and balancing delivery, risk, resiliency, and quality.

Descrição da oferta de emprego

Make banking a Fifth Third better®

We connect great people to great opportunities. Are you ready to take the next step? Discover a career in banking at Fifth Third Bank.

GENERAL FUNCTION:

The Principal Data Engineer designs and builds data platforms, tools, and solutions that enable the Bank to manage, secure, and extract value from its data. This role develops scalable, reusable solutions for collecting, storing, processing, and serving data across both traditional and modern architectures. Engineers work across on-premises and cloud-based environments to deliver reliable, secure, and well-governed data capabilities. The role includes leveraging AI-assisted engineering capabilities to improve productivity, code quality, testing, and documentation, while designing trusted data assets that support analytics, artificial intelligence, and machine learning use cases. Principal Data Engineers provide technical leadership across multiple teams within a business or data domain, independently deliver the most complex and high-impact solutions, shape technical strategy and standards, influence outcomes across the broader organization, and raise engineering capabilities through mentoring, coaching, and knowledge sharing.

Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and personally following policies and procedures as defined. Accountable for always doing the right thing for customers and colleagues while ensuring that actions and behaviors drive a positive customer experience. While operating within the Bank's risk appetite, achieves results by consistently identifying, assessing, managing, monitoring, and reporting risks of all types.

ESSENTIAL DUTIES & RESPONSIBILITIES:

• Responsible for design, development, and support of scalable data solutions, APIs, tools, and processes that enable rapid delivery of business capabilities across both traditional and modern data platforms.
• Work closely with IT application teams, Enterprise Architecture, infrastructure, information security, and LOB stakeholders to translate business and technical strategies into data-driven solutions, shape technical direction, and influence outcomes across multiple teams within a business or data domain with added impact across the broader organization.
• Act as a principal technical expert and trusted advisor addressing the most complex problems related to system and application design, performance, integration, security, and delivery.
• Conduct research and development based on current trends and technologies related to the banking industry, data engineering and architecture, data security, AI-readiness, and related topics, and translate relevant findings into practical improvements.
• Build and maintain CI/CD pipelines and self-service deployment tools to streamline development and operations.
• Evaluate data and software products, providing documented recommendations to improve capabilities.
• Lead ownership of the most complex and strategically important data solutions throughout their lifecycle, including design, development, testing, deployment, monitoring, operational support, modernization, and retirement, while defining and driving engineering standards across multiple teams.
• Provide support and troubleshooting for data pipelines and platforms, including participation in incident response and resolution for critical production issues.
• Lead strategic technical initiatives across multiple teams, including legacy system modernization, data pipeline improvements, monitoring, and documentation, while proactively identifying cross-team dependencies, risks, and barriers to delivery.
• Optimize and automate data pipelines for efficiency, scalability, observability, and performance.
• Develop and maintain automated testing, validation, reconciliation, and data quality controls to ensure reliable, trusted, and production-ready data solutions.
• Leverage approved AI-assisted engineering capabilities to improve productivity, code quality, testing, documentation, and problem solving, while supporting the delivery of trusted data assets for analytics, artificial intelligence, and machine learning solutions.
• Apply a data product mindset by managing the full lifecycle of data assets and ensuring appropriate ownership, quality, discoverability, documentation, lineage, and governance.
• Provide technical leadership, mentoring, coaching, and knowledge sharing across multiple teams, raising engineering competencies and contributing to greater effectiveness across the broader business or data domain and organization.
• Drive prioritization, escalation, and resolution of competing technical demands and strategic dependencies across multiple teams.
• Lead delivery of strategic, high-impact data solutions across multiple Agile teams through close collaboration with product owners and stakeholders, proactively removing cross-team barriers and balancing delivery, risk, resiliency, and quality.

SUPE